Table 6.
COVID-19 risk and the likelihood of loan default: the role of FinTech adoption
| Variables | DV = DEFAULT | ||
|---|---|---|---|
| (1) | (2) | (3) | |
| Panel A: high FinTech adoption | |||
| PANDEMIC_DUMMY |
0.267*** (0.007) |
||
| DAILY_CASES |
0.003*** (0.000) |
||
| DAILY_DEATHS |
0.025*** (0.001) |
||
| Loan originator individual effects | Yes | Yes | Yes |
| Controls | Yes | Yes | Yes |
| LR chi2 | 75,221.734 | 58,608.936 | 58,155.240 |
| Prob > chi2 | 0.000 | 0.000 | 0.000 |
| Pseudo-R-squared | 0.171 | 0.191 | 0.189 |
| N | 588,385 | 415,370 | 415,370 |
| Panel B: low FinTech adoption | |||
| PANDEMIC_DUMMY |
0.392*** (0.023) |
||
| DAILY_CASES |
0.009*** (0.001) |
||
| DAILY_DEATHS |
0.216*** (0.057) |
||
| Loan originator individual effects | Yes | Yes | Yes |
| Controls | Yes | Yes | Yes |
| LR chi2 | 10,252.819 | 5555.505 | 5532.129 |
| Prob > chi2 | 0.000 | 0.000 | 0.000 |
| Pseudo-R-squared | 0.164 | 0.219 | 0.218 |
| N | 226,487 | 87,783 | 87,783 |
Table reports the results for two panels. Panel A reports the findings of logit regression analysis for countries with high levels of FinTech adoption. Panel B reports the same findings for countries with low levels of FinTech adoption. The panels are based on countries’ FinTech Development Index (Findexable 2019) being higher/lower than the global median. All model specifications employ robust standard errors in parentheses (*p < 0.10, **p < 0.05, ***p < 0.01)